Computational Model of Ca(2+) Wave Propagation in Human Retinal Pigment Epithelial ARPE-19 Cells

OBJECTIVE: Computational models of calcium (Ca(2+)) signaling have been constructed for several cell types. There are, however, no such models for retinal pigment epithelium (RPE). Our aim was to construct a Ca(2+) signaling model for RPE based on our experimental data of mechanically induced Ca(2+) wave in the in vitro model of RPE, the ARPE-19 monolayer. METHODS: We combined six essential Ca(2+) signaling components into a model: stretch-sensitive Ca(2+) channels (SSCCs), P(2)Y(2) receptors, IP(3) receptors, ryanodine receptors, Ca(2+) pumps, and gap junctions. The cells in our epithelial model are connected to each other to enable transport of signaling molecules. Parameterization was done by tuning the above model components so that the simulated Ca(2+) waves reproduced our control experimental data and data where gap junctions were blocked. RESULTS: Our model was able to explain Ca(2+) signaling in ARPE-19 cells, and the basic mechanism was found to be as follows: 1) Cells near the stimulus site are likely to conduct Ca(2+) through plasma membrane SSCCs and gap junctions conduct the Ca(2+) and IP(3) between cells further away. 2) Most likely the stimulated cell secretes ligand to the extracellular space where the ligand diffusion mediates the Ca(2+) signal so that the ligand concentration decreases with distance. 3) The phosphorylation of the IP(3) receptor defines the cell’s sensitivity to the extracellular ligand attenuating the Ca(2+) signal in the distance. CONCLUSIONS: The developed model was able to simulate an array of experimental data including drug effects. Furthermore, our simulations predict that suramin may interfere ligand binding on P(2)Y(2) receptors or accelerate P(2)Y(2) receptor phosphorylation, which may partially be the reason for Ca(2+) wave attenuation by suramin. Being the first RPE Ca(2+) signaling model created based on experimental data on ARPE-19 cell line, the model offers a platform for further modeling of native RPE functions.